A practical control method for precision motion—Improvement of NCTF control method for continuous motion control

The present paper describes a practical control method for a precision motion system and the performance thereof. For practical use, high motion control performance and ease of design and controller adjustment are desired. A nominal characteristic trajectory following control (NCTF control) has been investigated to realize high performance and ease of application of point-to-point (PTP) positioning. The controller comprising a nominal characteristic trajectory (NCT) and a PI compensator is free from exact modeling and parameter identification. In the present paper, the NCTF control is modified in order to improve the control performance of continuous motions such as tracking and contouring motions. The NCTF controller for continuous motion (referred to as Continuous Motion NCTF controller) has a structure that is almost identical to the conventional NCTF controller and is designed using the same design procedure. The Continuous Motion NCTF controller is applied to ball screw mechanisms, and its motion control performance is evaluated from the experimental tracking, contouring, and positioning control results. The experimental results prove that the Continuous Motion NCTF controller achieves the same positioning performance as the conventional NCTF controller, and generally achieves better continuous motion control performances than PI-D or conventional NCTF controllers. In 0.25 Hz and 100-nm radius circular motion, the experimental tracking errors for Continuous Motion NCTF were smaller than 10 nm.     

T–S fuzzy model predictive speed control of electrical vehicles

This paper proposes a novel nonlinear model predictive controller (MPC) in terms of linear matrix inequalities (LMIs). The proposed MPC is based on Takagi–Sugeno (TS) fuzzy model, a non-parallel distributed compensation (non-PDC) fuzzy controller and a non-quadratic Lyapunov function (NQLF). Utilizing the non-PDC controller together with the Lyapunov theorem guarantees the stabilization issue of this MPC. In this approach, at each sampling time a quadratic cost function with an infinite prediction and control horizon is minimized such that constraints on the control input Euclidean norm are satisfied. To show the merits of the proposed approach, a nonlinear electric vehicle (EV) system with parameter uncertainty is considered as a case study. Indeed, the main goal of this study is to force the speed of EV to track a desired value. The experimental data, a new European driving cycle (NEDC), is used in order to examine the performance of the proposed controller. First, the equivalent TS model of the original nonlinear system is derived. After that, in order to evaluate the proficiency of the proposed controller, the achieved results of the proposed approach are compared with those of the conventional MPC controller and the optimal Fuzzy PI controller (OFPI), which are the latest research on the problem in hand.     

Gear fault identification based on Hilbert–Huang transform and SOM neural network

Gear vibration signals always display non-stationary behavior. HHT (Hilbert–Huang transform) is a method for adaptive analysis of non-linear and non-stationary signals, but it can only distinguish conspicuous faults. SOM (self-organizing feature map) neural network is a network learning with no instructors which has self-adaptive and self-learning features and can compensate for the disadvantage of HHT. This paper proposed a new gear fault identification method based on HHT and SOM neural network. Firstly, the frequency families of gear vibration signals were separated effectively by EMD (empirical mode decomposition). Then Hilbert spectrum and Hilbert marginal spectrum were obtained by Hilbert transform of IMFs (intrinsic mode functions). The amplitude changes of gear vibration signals along with time and frequency had been displayed respectively. After HHT, the energy percentage of the first six IMFs were chosen as input vectors of SOM neural network for fault classification. The analysis results showed that the fault features of these signals can be accurately extracted and distinguished with the proposed approach.     

Robust sliding mode control for uncertain servo system using friction observer and recurrent fuzzy neural networks?

A robust positioning control scheme has been developed using friction parameter observer and recurrent fuzzy neural networks based on the sliding mode control. As a dynamic friction model, the LuGre model is adopted for handling friction compensation because it has been known to capture sufficiently the properties of a nonlinear dynamic friction. A developed friction parameter observer has a simple structure and also well estimates friction parameters of the LuGre friction model. In addition, an approximation method for the system uncertainty is developed using recurrent fuzzy neural networks technology to improve the precision positioning degree. Some simulation and experiment provide the verification on the performance of a proposed robust control scheme.     

Improving control and estimation for distributed parameter systems utilizing mobile actuator–sensor network

This paper proposes a scheme for non-collocated moving actuating and sensing devices which is unitized for improving performance in distributed parameter systems. By Lyapunov stability theorem, each moving actuator/sensor agent velocity is obtained. To enhance state estimation of a spatially distributes process, two kinds of filters with consensus terms which penalize the disagreement of the estimates are considered. Both filters can result in the well-posedness of the collective dynamics of state errors and can converge to the plant state. Numerical simulations demonstrate that the effectiveness of such a moving actuator–sensor network in enhancing system performance and the consensus filters converge faster to the plant state when consensus terms are included.     

A flexible artificial neural network–fuzzy simulation algorithm for scheduling a flow shop with multiple processors

One of the most popular approaches for scheduling manufacturing systems is dispatching rules. Different types of dispatching rules exist, but none of them is known to be globally the best. A flexible artificial neural network–fuzzy simulation (FANN–FS) algorithm is presented in this study for solving the multiattribute combinatorial dispatching (MACD) decision problem. Artificial neural networks (ANNs) are one of the commonly used metaheuristics and are a proven tool for solving complex optimization problems. Hence, multilayered neural network metamodels and a fuzzy simulation using the α-cuts method were trained to provide a complex MACD problem. Fuzzy simulation is used to solve complex optimization problems to deal with imprecision and uncertainty. The proposed flexible algorithm is capable of modeling nonlinear, stochastic, and uncertain problems. It uses ANN simulation for crisp input data and fuzzy simulation for imprecise and uncertain input data. The solution quality is illustrated by two case studies from a multilayer ceramic capacitor manufacturing plant. The manufacturing lead times produced by the FANN–FS model turned out to be superior to conventional simulation models. This is the first study that introduces an intelligent and flexible approach for handling imprecision and nonlinearity of scheduling problems in flow shops with multiple processors.     

Robust H(∞) control of uncertain switched systems defined on polyhedral sets with Filippov solutions

This paper considers the control problem of a class of uncertain switched systems defined on polyhedral sets known as piecewise linear systems where, instead of the conventional Carathéodory solutions, Filippov solutions are studied. In other words, in contrast to the previous studies, solutions with infinite switching in finite time along the facets and on faces of arbitrary dimensions are also taken into account. Firstly, established upon previous studies, a set of linear matrix inequalities are brought forward which determines the asymptotic stability of piecewise linear systems with Filippov solutions. Subsequently, bilinear matrix inequality conditions for synthesizing a robust controller with a guaranteed H(∞) performance are presented. Furthermore, these results has been generalized to the case of piecewise affine systems. Finally, a V-K iteration algorithm is proposed to deal with the aforementioned bilinear matrix inequalities. The validity of the proposed method is verified through the analysis of two simulation examples.     

Takagi–Sugeno fuzzy model based robust dissipative control for uncertain flexible spacecraft with saturated time-delay input

In this paper, the problem of robust dissipative control is investigated for uncertain flexible spacecraft based on Takagi–Sugeno (T–S) fuzzy model with saturated time-delay input. Different from most existing strategies, T–S fuzzy approximation approach is used to model the nonlinear dynamics of flexible spacecraft. Simultaneously, the physical constraints of system, like input delay, input saturation, and parameter uncertainties, are also taken care of in the fuzzy model. By employing Lyapunov–Krasovskii method and convex optimization technique, a novel robust controller is proposed to implement rest-to-rest attitude maneuver for flexible spacecraft, and the guaranteed dissipative performance enables the uncertain closed-loop system to reject the influence of elastic vibrations and external disturbances. Finally, an illustrative design example integrated with simulation results are provided to confirm the applicability and merits of the developed control strategy.     

Synthesis and optical properties research of gold nanoparticles with different morphologies

本文制备了不同形貌的金纳米颗粒,并对其形貌对光学性能的影响进行了研究。本文用还原法制备了不同粒径的金纳米颗粒,采用晶种生长法成功地制备出了星形、梭形和棒状的金纳米颗粒。颗粒的形貌和大小并采用投射电子显微镜(TEM)进行了表征,结果说明,本文成功制备出了不同形貌大小的金纳米颗粒。UV-Vis光谱和拉曼光谱仪对制备的颗粒的表征测试说明,不同形貌大小对颗粒有着不同的光学性能。拉曼光谱的结果说明,不同形貌大小的金纳米颗粒可以用作不同浓度分子的探针,对物质进行检测。     

H∞ non-fragile observer-based dynamic event-triggered sliding mode control for nonlinear networked systems with sensor saturation and dead-zone input

This paper considers the problem of robust non-fragile observer-based dynamic event-triggered sliding mode control (SMC) for a class of discrete-time Lipschitz nonlinear networked control systems subject to sensor saturation and dead-zone input nonlinearity. First, an improved dynamic event-triggered scheme (DETS) in consideration of sensor saturation is proposed to reduce the number of data transmission. Next, a non-fragile observer is designed to estimate the system state, which facilitates the construction of the discrete sliding surface. By using a reformulated Lipschitz property, the error dynamics and sliding mode dynamics are modeled as a unified linear parameter varying (LPV) networked system with time-varying delays. Then, based on this model, sufficient conditions are established to guarantee the resulting closed-loop system to be asymptotically stable with a given disturbance attenuation level. Furthermore, an observer-based event-triggered SMC law is designed to drive the trajectories of the observer system onto a region near equilibrium point in a finite time in the presence of dead-zone input nonlinearity. Finally, two practical examples are employed to demonstrate the effectiveness of the proposed method.     

Chip perforation and ‘burnishing–like’ finishing of Al alloy in precision machining

In precision machining, a high quality machined surface cannot be achieved without using a diamond tool, due to the deterioration of workpiece surface integrity. Burnishing process is often used to improve the surface integrity by minimizing the roughness of the machined surface. For any given cutting tool-workpiece combination, the surface roughness depends on a parameter known as relative tool sharpness (RTS), which is quantified as the ratio of undeformed chip thickness (a) to tool edge radius (r). To achieve burnishing-like surface quality from precision machining, it is necessary to understand the material deformation behaviour in machining. Moreover, the quality of the machined surface is also directly related to the formation of μ-chip and its geometry. Thus, in this study, an attempt has been undertaken to develop the behavioural chip formation mechanics for the transition from unstable to the stable regime. Orthogonal microcutting experiments have been conducted with Al alloy (Al 6082) workpiece to investigate the micro-mechanics of chip perforation and to develop the chip stability mapping. Furthermore, the quantitative assessment criterion has been adopted to determine the material flow stress, which augmented the investigation of the burnishing-like deformation behaviour. By appraising the factors like machined surface integrity, compressive flow stress and improvement of surface roughness (R_a) profile, a ‘burnishing-like’ finishing zone has been identified. Additionally, SEM and EDX analyses have been performed to study the elemental composition of μ-chips, which allowed to validate the transition phenomena of chip perforation from incomplete (unstable) to complete (stable) chip formation. The applicability of this novel study lies in its ability to produce superior quality machined surface without requiring a secondary finishing operation and thus, improving the performance of precision machining.     

Wear behavior of Cu–La2O3 composite with or without electrical current

A new type Cu–La₂O₃ composite was fabricated by internal oxidation method using powder metallurgy. Sliding wear behavior of the Cu–La₂O₃ composites was studied by using a pin-on-disk wear tester under dry sliding conditions with or without electrical current, rubbing against GCr15 type bearing steel disk at a constant sliding speed of 20 m/s. The influence of varying applied load and electrical current was investigated. The worn surfaces were examined using scanning electron microscopy (SEM) and energy dispersive spectroscopy (EDS) to determine the wear mechanisms. The results showed the Cu–La₂O₃ composites had an electrical conductivity of 81.9% IACS (International Annealed Copper Standard, 100% IACS = 58 MS/m) and a hardness of HV105. The wear rate of the Cu–La₂O₃ composite pins increased with the increase in the electrical current at high sliding speed. The main wear mechanisms of the Cu–La₂O₃ composites were found to be adhesive wear, abrasive wear and arc erosion.     

Application of general regression neural network (GRNN) for indirect measuring pressure loss of Herschel–Bulkley drilling fluids in oil drilling

Experimental measurements of the pressure losses in a well annulus are costly and time consuming. Pressure loss calculations in annulus is generally conducted based on an extension of empirical correlations developed for Newtonian fluids and extending pipe flow correlations. However, correct estimation of pressure loss of non-Newtonian fluids in oil well drilling operations is very important for optimum design of piping system and minimizing the power consumption. In this paper, a general regression neural network (GRNN) was applied to predict the pressure loss of Herschel–Bulkley drilling fluids in concentric and eccentric annulus. Experimental data from literature were used to train the GRNN for estimating pressure losses in annulus. The predicted values using GRNN closely followed the experimental ones with an average relative absolute error less than 6.24%, and correlation coefficient (R) of 0.99 for pressure loss estimation.     

Performance and surface alloying characteristics of Cu–Cr and Cu–Mo powder metal tool electrodes in electrical discharge machining

The main objective of this study is to investigate the effect of Cu–Cr and Cu–Mo powder metal (PM) tool electrodes on electrical discharge machining (EDM) performance outputs. The EDM performance measures used in the study are material removal rate (MRR), tool electrode wear rate (EWR), average workpiece surface roughness (R_a), machined workpiece surface hardness, abrasive wear resistance, corrosion resistance, and workpiece alloyed layer depth and composition. The EDM performance of Cu–Cr and Cu–Mo PM electrodes produced at three different mixing ratios (15, 25, and 35 wt% Cr or Mo), compacting pressures (P_c = 600, 700, and 800 MPa), and sintering temperatures (T_s = 800, 850, and 900 °C) are compared with those machined with electrolytic Cu and Cu PM electrodes when machining SAE 1040 steel workpiece. Analyses revealed that tool materials were deposited as a layer over the work surface yielding high surface hardness, strong abrasion, and corrosion resistance. Moreover, the mixing ratio, P_c, and T_s affect the MRR, EWR, and R_a values.     

Lubrication of aluminium–silicon surfaces with ZDDP and detergents

Abstract

A review of the lubrication of aluminium–silicon (Al-Si) substrates by zinc dialkyldithiophosphate (ZDDP) and detergent engine oil additives is presented. Greater attention has been paid to understand the interactions of ZDDP, rather than detergents, with the aforementioned non-ferrous substrates. Zinc dialkyldithiophosphate generates tribofilms on both aluminium and silicon regions of aluminium–silicon alloys. However, film formation is believed to occur on silicon grains within the alloy, and those layers observed on aluminium regions are material transfer or the product of ZDDP thermal decomposition. There were many similarities in terms of film thickness, reduced elastic modulus, tribochemistry and topography of ZDDP derived tribofilms on both ferrous and Al–Si substrates. Calcium carbonate based films were observed on silicon grains when the aluminium alloys were lubricated with overbased calcium sulphonate, the tribochemistry and topography of which were similar to layers formed on ferrous substrates. When lubricated with either fully formulated oil or lubricants containing both detergent and ZDDP, the subsequently generated films were of varying chemistry, but often contained zinc or calcium phosphate compounds. The antiwear characteristics of ZDDP and calcium sulphonate tribofilms on ferrous and aluminium–silicon substrates are discussed, with the mechanical and film thickness data for such layers presented.     

Effect of deformation martensite on the electrical and magnetic properties of plastically deformed chromium–nickel steel

Connection between the structural and phase changes in specimens of chromium–nickel austenitic steel and their magnetic and electrical properties has been studied. It has been established that electric resistivity can be used as an additional testing parameter for the phase composition of plastically deformed articles made of austenitic-ferritic steel. It has been shown that the emergence of an additional phase of strain-induced martensite leads to a significant increase in electric resistivity.     

Experimental validation of PID based cascade control system through SCADA–PLC–OPC and internet architectures

The paper presents the experimental validation procedure of a simple cascade control system through number of architectures, such as SCADA, PLC, OPC and internet. The performance and effectiveness of individual architecture is evaluated on the basis of data rate, rise time, peak time and settling time. In this study, PID is implemented on Micrologix-1200 PLC and RSView-32 SCADA has been used with RSLinx communication software. The PLC–SCADA control loop is implemented with the functionalities such as, real time data analysis, set point modifications, automatic report generation and integration of data with MS-Excel and MS-Access. The enhancement in project data analysis is effectively done through the integration of PLC with Labview. The remote monitoring and control of process parameters is done using NET-ENI. The obtained result proved that the conventional SCADA based control system can be enhanced further more with PLC as well as NI-OPC server significantly.